Machine learning post-treatment survey data organizing

Abstract

Described herein are techniques, methods, systems, apparatus, and computer program products for processing post-treatment survey data for care providers. In certain embodiments, machine learning is utilized to provide a technique that removes identifying information from post-treatment surveys, in order to conform with professional ethics requirements. In another embodiment, a system for providing post-treatment surveys and determining feedback accordingly is provided.

What is claimed is: 
     
         1 . A method comprising:
 receiving training data, wherein the training data is associated with post-treatment satisfaction surveys;   classifying portions of the training data as, at least, identifying sections or non-identifying sections;   training, with the identifying sections, a first machine learning model to determine identifying data of surveys;   training, with the non-identifying sections, a second machine learning model to determine an improvement point;   receiving a first post-treatment satisfaction survey associated with a patient of a provider;   determining, with the first machine learning model, one or more identifying data sections of the first post-treatment satisfaction survey;   anonymizing the identifying data sections of the first post-treatment satisfaction survey to create an anonymized first post-treatment satisfaction survey;   analyzing the anonymized first post-treatment satisfaction survey to determine an improvement point for the provider; and   outputting the improvement point to a user device of the provider.   
     
     
         2 . The method of  claim 1 , further comprising:
 determining that a treatment for the patient has finished;   determining that the patient is authorized to receive the first post-treatment satisfaction survey; and   providing, based on the determining that the treatment of the patient has finished and that the patient is authorized to receive the first post-treatment satisfaction survey, the first post-treatment satisfaction survey to an electronic device associated with the patient.   
     
     
         3 . The method of  claim 1 , further comprising:
 determining, based on the improvement point, a first course associated with the improvement point, wherein the outputting the improvement point comprises providing data associated with the first course.   
     
     
         4 . The method of  claim 1 , further comprising:
 identifying, from data within an electronic health record (EHR) database and based on the improvement point, a first service associated with the improvement point, wherein the outputting the improvement point comprises providing data associated with the first service.   
     
     
         5 . The method of  claim 1 , wherein the determining the identifying data comprises determining a name, a date, and/or a description of treatment. 
     
     
         6 . The method of  claim 1 , wherein the anonymizing the identifying data sections comprises converting textual responses of the first post-treatment satisfaction survey to a response category and a response rating. 
     
     
         7 . The method of  claim 1 , further comprising:
 determining a location of the patient, wherein the analyzing the anonymized first post-treatment satisfaction survey is based on the location, wherein the analyzing the anonymized first post-treatment satisfaction survey based on the location comprises determining the improvement point based on the location.   
     
     
         8 . The method of  claim 1 , wherein the classifying portions of the training data further comprises classifying portions of testimonial data as numerical, essay, and/or testimonial data. 
     
     
         9 . A system comprising:
 a electronic health record (EHR) database;   a communications interface, communicatively coupled to the electronic health record (EHR) database via a network;   a processor, communicatively coupled to the communications interface and the EHR database and configured to cause the system to perform operations comprising:
 receiving, with the communications interface, treatment process data from the EHR database; 
 determining, from the treatment process data, that a treatment for a first patient with a first provider has finished; 
 causing, based on the determining that the treatment for the first patient has finished, a first post-treatment satisfaction survey to be provided to an electronic device of the first patient; 
 receiving a first survey, wherein the first survey is a response to the first post-treatment satisfaction survey; 
 dividing the first survey into identifying sections and non-identifying sections; 
 removing the identifying sections; 
 determining, based on the non-identifying sections, a first improvement point for the first provider; 
 determining, from course data stored within the EHR database and based on the first improvement point, a first course associated with the first improvement point; and 
 transmitting first course data associated with the first course to a user device of the first provider. 
   
     
     
         10 . The system of  claim 9 , wherein the operations further comprise:
 receiving a training data;   classifying portions of the training survey as, at least, identifying sections or non-identifying sections;   training, with the identifying sections, a first machine learning model to determine identifying data of surveys; and   training, with the non-identifying sections, a second machine learning model to determine an improvement point for the provider.   
     
     
         11 . The system of  claim 10 , wherein the dividing the first survey into the identifying sections and the non-identifying sections comprises determining, with the first machine learning model, one or more identifying data sections of the first survey, and wherein the removing the identifying sections comprises anonymizing the identifying data sections of the first survey to create an anonymized first survey. 
     
     
         12 . The system of  claim 11 , wherein the determining the one or more identifying data comprises determining a name, a date, and/or a description of a treatment procedure within the first survey. 
     
     
         13 . The system of  claim 11 , wherein the anonymizing the identifying data sections comprises converting textual responses of the first survey to a response category and a response rating. 
     
     
         14 . The system of  claim 11 , wherein the determining the first improvement point comprises analyzing the anonymized first survey. 
     
     
         15 . The system of  claim 14 , wherein the operations further comprise:
 determining a location of the patient, wherein the analyzing the anonymized first survey is based on the location, wherein the first improvement point is determined based on the location.   
     
     
         16 . The system of  claim 9 , wherein the dividing the first survey further comprises dividing into numerical, essay, and/or testimonial sections. 
     
     
         17 . The system of  claim 9 , wherein the operations further comprise:
 identifying, from service data stored within the DAR database and based on the first improvement point, a first service associated with the improvement point; and   transmitting first service data to the user device of the first provider.   
     
     
         18 . A computer program product comprising computer-readable program code capable of being executed by one or more processors when retrieved from a non-transitory computer-readable medium, the program code comprising instructions configurable to cause operations comprising:
 receiving a training data;   classifying portions of the training data as, at least, identifying sections or non-identifying sections;   training, with the identifying sections, a first machine learning model to determine identifying data of surveys;   training, with the non-identifying sections, a second machine learning model to determine an improvement point;   receiving a first post-treatment satisfaction survey associated with a patient of a provider;   determining, with the first machine learning model, one or more identifying data sections of the first post-treatment satisfaction survey;   anonymizing the identifying data sections of the first post-treatment satisfaction survey to create an anonymized first post-treatment satisfaction survey;   analyzing the anonymized first post-treatment satisfaction survey to determine an improvement point for the provider; and
 outputting the improvement point to a user device of the provider. 
   
     
     
         19 . The computer program product of  claim 18 , wherein the operations further comprise:
 determining that a treatment for the patient has finished;   determining that the patient is authorized to receive the first post-treatment satisfaction survey; and   providing, based on the determining that the treatment of the patient has finished, the first post-treatment satisfaction survey to an electronic device associated with the patient.   
     
     
         20 . The computer program product of  claim 18 , wherein the operations further comprise:
 determining, based on the improvement point, a first course associated with the improvement point, wherein the outputting the improvement point comprises providing data associated with the first course.